Innovative Data Anomaly Detection and Transformation for Analysis Applications

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$80,000.00
Award Year:
2014
Program:
SBIR
Phase:
Phase I
Contract:
N68335-14-C-0091
Award Id:
n/a
Agency Tracking Number:
N132-096-0399
Solicitation Year:
2013
Solicitation Topic Code:
N132-096
Solicitation Number:
2013.2
Small Business Information
215 Parkway North, P.O. Box 280, Waterford, CT, 06385-
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
077317766
Principal Investigator:
Margaret Bailey
Principal Investigator
(860) 326-3621
bailey_m@sonalysts.com
Business Contact:
Christopher Cote
Contracting Officer
(860) 326-3932
ccote@sonalysts.com
Research Institution:
n/a
Abstract
NAVAIR"s Warfare Analysis and Integration Department (AIR 4.10) has three labor intensive, error prone, data management operations that Sonalysts"desktop, Windows application will automate with a generic toolkit to greatly reduce the human effort. The data provided by the fleet tends to be error prone, but modeling, simulation, and analysis require valid data. The data contains both quantitative and qualitative elements which are interdependent. Additionally, these processes must be run on hypothetical datasets to evaluate proposed equipment changes, where the potential benefits are loosely defined. Once the data is cleaned, the results need to be formatted to support downstream analysis tools. The codes, rules, and formats evolve over time. Sonalysts proposes a set of user-configurable, rule-set generators for creating and maintaining instructions for cleaning the data, synthesizing hypothetical data, and formatting output datasets. These rule sets are used by the code, but are not part of it. Thus, modifications do not require program source code changes or recompiling. Qualitative data analysis techniques will be used to perform weighted matching of text elements to automate selection of dependent code values.

* information listed above is at the time of submission.

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